Why we need schema
Some NoSQL databases or message queue are not strongly limited schema, so the schema cannot be obtained through the api. At this time, a schema needs to be defined to convert to TableSchema and obtain data.
SchemaOptions
We can use SchemaOptions to define schema, the SchemaOptions contains some config to define the schema. e.g. columns, primaryKey, constraintKeys.
schema = {
table = "database.schema.table"
schema_first = false
comment = "comment"
columns = [
...
]
primaryKey {
...
}
constraintKeys {
...
}
}
table
The table full name of the table identifier which the schema belongs to, it contains database, schema, table name. e.g. database.schema.table
, database.table
, table
.
schema_first
Default is false.
If the schema_first is true, the schema will be used first, this means if we set table = "a.b"
, a
will be parsed as schema rather than database, then we can support write table = "schema.table"
.
comment
The comment of the CatalogTable which the schema belongs to.
Columns
Columns is a list of config used to define the column in schema, each column can contains name, type, nullable, defaultValue, comment field.
columns = [
{
name = id
type = bigint
nullable = false
columnLength = 20
defaultValue = 0
comment = "primary key id"
}
]
Field | Required | Default Value | Description |
---|---|---|---|
name | Yes | - | The name of the column |
type | Yes | - | The data type of the column |
nullable | No | true | If the column can be nullable |
columnLength | No | 0 | The length of the column which will be useful when you need to define the length |
columnScale | No | - | The scale of the column which will be useful when you need to define the scale |
defaultValue | No | null | The default value of the column |
comment | No | null | The comment of the column |
What type supported at now
Data type | Value type in Java | Description |
---|---|---|
string | java.lang.String |
string |
boolean | java.lang.Boolean |
boolean |
tinyint | java.lang.Byte |
-128 to 127 regular. 0 to 255 unsigned*. Specify the maximum number of digits in parentheses. |
smallint | java.lang.Short |
-32768 to 32767 General. 0 to 65535 unsigned*. Specify the maximum number of digits in parentheses. |
int | java.lang.Integer |
All numbers from -2,147,483,648 to 2,147,483,647 are allowed. |
bigint | java.lang.Long |
All numbers between -9,223,372,036,854,775,808 and 9,223,372,036,854,775,807 are allowed. |
float | java.lang.Float |
Float-precision numeric data from -1.79E+308 to 1.79E+308. |
double | java.lang.Double |
Double precision floating point. Handle most decimals. |
decimal | java.math.BigDecimal |
DOUBLE type stored as a string, allowing a fixed decimal point. |
null | java.lang.Void |
null |
bytes | byte[] |
bytes. |
date | java.time.LocalDate |
Only the date is stored. From January 1, 0001 to December 31, 9999. |
time | java.time.LocalTime |
Only store time. Accuracy is 100 nanoseconds. |
timestamp | java.time.LocalDateTime |
Stores a unique number that is updated whenever a row is created or modified. timestamp is based on the internal clock and does not correspond to real time. There can only be one timestamp variable per table. |
row | org.apache.seatunnel.api.table.type.SeaTunnelRow |
Row type,can be nested. |
map | java.util.Map |
A Map is an object that maps keys to values. The key type includes int string boolean tinyint smallint bigint float double decimal date time timestamp null , and the value type includes int string boolean tinyint smallint bigint float double decimal date time timestamp null array map row . |
array | ValueType[] |
A array is a data type that represents a collection of elements. The element type includes int string boolean tinyint smallint bigint float double . |
How to declare type supported
SeaTunnel provides a simple and direct way to declare basic types. Basic type keywords include string
, boolean
, tinyint
, smallint
, int
, bigint
, float
, double
, date
, time
, timestamp
, and null
. The keyword names for basic types can be used directly as type declarations, and SeaTunnel is case-insensitive to type keywords. For example, if you need to declare a field with integer type, you can simply define the field as int
or "int"
.
The null type declaration must be enclosed in double quotes, like
"null"
. This approach helps avoid confusion with HOCON‘snull
type which represents undefined object.
When declaring complex types (such as decimal, array, map, and row), pay attention to specific considerations.
- When declaring a decimal type, precision and scale settings are required, and the type definition follows the format
decimal(precision, scale)
. It’s essential to emphasize that the declaration of the decimal type must be enclosed in"
; you cannot use the type name directly, as with basic types. For example, when declaring a decimal field with precision 10 and scale 2, you specify the field type as"decimal(10,2)"
. - When declaring an array type, you need to specify the element type, and the type definition follows the format
array<T>
, whereT
represents the element type. The element type includesint
,string
,boolean
,tinyint
,smallint
,bigint
,float
anddouble
. Similar to the decimal type declaration, it also be enclosed in"
. For example, when declaring a field with an array of integers, you specify the field type as"array<int>"
. - When declaring a map type, you need to specify the key and value types. The map type definition follows the format
map<K,V>
, whereK
represents the key type andV
represents the value type.K
can be any basic type and decimal type, andV
can be any type supported by SeaTunnel. Similar to previous type declarations, the map type declaration must be enclosed in double quotes. For example, when declaring a field with map type, where the key type is string and the value type is integer, you can declare the field as"map<string, int>"
. - When declaring a row type, you need to define a HOCON object to describe the fields and their types. The field types can be any type supported by SeaTunnel. For example, when declaring a row type containing an integer field
a
and a string fieldb
, you can declare it as{a = int, b = string}
. Enclosing the definition in"
as a string is also acceptable, so"{a = int, b = string}"
is equivalent to{a = int, c = string}
. Since HOCON is compatible with JSON,"{\"a\":\"int\", \"b\":\"string\"}"
is equivalent to"{a = int, b = string}"
.
Here is an example of complex type declarations:
schema {
fields {
c_decimal = "decimal(10, 2)"
c_array = "array<int>"
c_row = {
c_int = int
c_string = string
c_row = {
c_int = int
}
}
# Hocon style declare row type in generic type
map0 = "map<string, {c_int = int, c_string = string, c_row = {c_int = int}}>"
# Json style declare row type in generic type
map1 = "map<string, {\"c_int\":\"int\", \"c_string\":\"string\", \"c_row\":{\"c_int\":\"int\"}}>"
}
}
PrimaryKey
Primary key is a config used to define the primary key in schema, it contains name, columns field.
primaryKey {
name = id
columns = [id]
}
Field | Required | Default Value | Description |
---|---|---|---|
name | Yes | - | The name of the primaryKey |
columns | Yes | - | The column list in the primaryKey |
ConstraintKeys
Constraint keys is a list of config used to define the constraint keys in schema, it contains constraintName, constraintType, constraintColumns field.
constraintKeys = [
{
constraintName = "id_index"
constraintType = KEY
constraintColumns = [
{
columnName = "id"
sortType = ASC
}
]
},
]
Field | Required | Default Value | Description |
---|---|---|---|
constraintName | Yes | - | The name of the constraintKey |
constraintType | No | KEY | The type of the constraintKey |
constraintColumns | Yes | - | The column list in the primaryKey, each column should contains constraintType and sortType, sortType support ASC and DESC, default is ASC |
What constraintType supported at now
ConstraintType | Description |
---|---|
INDEX_KEY | key |
UNIQUE_KEY | unique key |
How to use schema
Recommended
source {
FakeSource {
parallelism = 2
result_table_name = "fake"
row.num = 16
schema {
table = "FakeDatabase.FakeTable"
columns = [
{
name = id
type = bigint
nullable = false
defaultValue = 0
comment = "primary key id"
},
{
name = name
type = "string"
nullable = true
comment = "name"
},
{
name = age
type = int
nullable = true
comment = "age"
}
]
primaryKey {
name = "id"
columnNames = [id]
}
constraintKeys = [
{
constraintName = "unique_name"
constraintType = UNIQUE_KEY
constraintColumns = [
{
columnName = "name"
sortType = ASC
}
]
},
]
}
}
}
Deprecated
If you only need to define the column, you can use fields to define the column, this is a simple way but will be remove in the future.
source {
FakeSource {
parallelism = 2
result_table_name = "fake"
row.num = 16
schema = {
fields {
id = bigint
c_map = "map<string, smallint>"
c_array = "array<tinyint>"
c_string = string
c_boolean = boolean
c_tinyint = tinyint
c_smallint = smallint
c_int = int
c_bigint = bigint
c_float = float
c_double = double
c_decimal = "decimal(2, 1)"
c_bytes = bytes
c_date = date
c_timestamp = timestamp
}
}
}
}
When we should use it or not
If there is a schema
configuration project in Options,the connector can then customize the schema. Like Fake
Pulsar
Http
source connector etc.